New Database Spanning Hundreds of Wind Test Reports

Managers of large-scale wind farm portfolios are faced with a veritable flood of information throughout the life-cycle of their wind turbines. In addition to electronically transmitted data from turbine operation, documents including permits, invoices and maintenance and repair reports all contain important details that can help to optimise operation. The regular reports from periodic inspections also deliver valuable information concerning the actual condition of the equipment.

However, the enormous volume of this information often makes it difficult to draw the right conclusions from the data, and thus to make the correct investment decisions. Do the turbines have any damage or faults that must be repaired immediately? What about general repair and maintenance procedures, and the time limits that apply to them? While operating and documentation processes may ensure that the relevant data and information is collected, it is often not easy to process. Letters and PDF files, for instance, often do not have the necessary interfaces and export functions. For this reason, data and information are frequently entered in other IT systems or file formats (e.g. Excel spreadsheets) to enable them to be evaluated, priorities to be assigned to activities and work to be commissioned on the turbines.

Exploiting the benefits of digitisation

A standardised and digitised method of processing information can thus offer a host of advantages. One area which benefits from digitisation is the evaluation of data from periodic turbine testing and inspection reports. In the past, faults or defects have usually been noted in a paper checklist and then entered by the expert in individual IT systems and file formats. However, this method soon generates many hundreds of test reports; as an additional problem, details are often not consistently recorded during on-site inspections. Differing descriptions, names, synonyms or abbreviations may be used for one and the same component, and descriptions of concrete faults may be imprecise or recorded in insufficient detail.

The industry has already taken the first steps towards improving the system by introducing standardisation and eliminating scope for personal interpretation. As an example, the European Technical Association for Power and Heat Generation (VGB) has drawn up the “Reference Designation System for Power Plants” (RDS-PP ®) for wind turbines. In this system, the methods and nomenclature are based on KKS, the proven German system for large-scale power plant designation. Each component is allocated a unique code depending on its function and location of installation; for example, azimuth motors have the code MDL 10.

This innovation has now been used as the basis of a new database solution developed by experts at TÜV SÜD. Fault data from periodic tests and inspections can be recorded in a standardised digital manner on site, using a mobile device such as a smartphone or tablet. The inspectors click on the requisite entries in an extensive catalogue of codes. This enables faults to be precisely described, while also identifying the specific components and their location.

In addition to the testing and inspection reports – which turbine operators can manage as accustomed in netDocX, the electronic log – they can also access the database, a central repository of all information and details which is intelligently structured to provide operators with a rapid overview of the condition of their turbines. These functions not only support operators in their data analysis and evaluation, but also allow them to produce statistics, derive forecasts, prioritise activities and manage deadlines and tasks.

In addition, the design of the new software now enables more in-depth analyses to be produced, which would involve enormous effort using conventional tools – if, indeed, they were even possible. As documented faults can now be presented as general trends, turbine operators can rapidly identify clusters such as the most frequent defects, any increased occurrence of failure in components from individual manufacturers, or an incidence of specific faults in certain systems or regions (e.g. lightning damage). Serial defects can likewise be quickly spotted. Operating managers can plan their maintenance and repair works with greater precision, and quantify individual damage types in financial terms. The new method reduces downtime, boosts efficiency and simplifies budget planning.

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